Apply it to your data 4

Which of your stock beat the market in 2022?

1 Import stock prices of your choice

## # A tibble: 6,290 × 8
##    symbol date        open  high   low close   volume adjusted
##    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>    <dbl>    <dbl>
##  1 MSFT   2012-01-03  26.5  27.0  26.4  26.8 64731500     21.2
##  2 MSFT   2012-01-04  26.8  27.5  26.8  27.4 80516100     21.7
##  3 MSFT   2012-01-05  27.4  27.7  27.3  27.7 56081400     21.9
##  4 MSFT   2012-01-06  27.5  28.2  27.5  28.1 99455500     22.2
##  5 MSFT   2012-01-09  28.0  28.1  27.7  27.7 59706800     21.9
##  6 MSFT   2012-01-10  27.9  28.1  27.8  27.8 60014400     22.0
##  7 MSFT   2012-01-11  27.4  28.0  27.4  27.7 65582400     21.9
##  8 MSFT   2012-01-12  27.9  28.0  27.6  28   49370800     22.1
##  9 MSFT   2012-01-13  27.9  28.2  27.8  28.2 60196100     22.3
## 10 MSFT   2012-01-17  28.4  28.6  28.2  28.3 72395300     22.3
## # ℹ 6,280 more rows

2 Convert prices to returns by quarterly

3 Make plot

## $y
## [1] "Frequency"
## 
## $x
## [1] "Rate of Returns"
## 
## $title
## [1] "Distribution of Quarterly Returns, 2021-2016"
## 
## $caption
## [1] "A typic monthly return is higher for MSFT and AAPL than for F, JPM, and SBUX"
## 
## attr(,"class")
## [1] "labels"

4 Interpret the plot

SBUX has the highest potential returns with a wider range, especially in the positive area. AAPL and F have more moderate returns, mostly centered around zero. MSFT and JP* show a balanced distribution with some potential for gains but not as high as SBUX.

5 Change the global chunck options

Hide the code, messages, and warnings